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Analysis of Information Propagation Characteristics in a Class of Three-layer Coupled Networks

Published: 19 September 2022 Publication History

Abstract

In order to reveal the cross-platform communication characteristics of information in social networks, a three-layer coupled network communication model (TCNM) of "user layer-medium layer-platform layer" is constructed using the SIR communication mechanism and social behavior characteristics, and the three categories of node nearest neighbor, node path and node feature vector are used to determine the node importance and seven indicators to select the communication sources, and the correlation between inter-layer coupling mechanism and communication conditions, communication period and peak value is analyzed. Combined with the experiments, it is concluded that the stronger the inter-layer coupling, the shorter the information propagation period, the faster the peak and the higher the peak; when the inter-layer coupling is weak, the information propagation is fastest when the source is in the platform layer, and the period is smallest and the peak is highest when it is in the media layer. The choice of different source indicators has different effects on the information dissemination cycle and peak value.

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ICCMS '22: Proceedings of the 14th International Conference on Computer Modeling and Simulation
June 2022
271 pages
ISBN:9781450396547
DOI:10.1145/3547578
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 19 September 2022

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  • the Science and Technology Department of Qinghai Province
  • the National Natural Science Foundation of China

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